Improvements in balance reaction impairments following reactive balance training in individuals with sub-acute stroke: A prospective cohort study with historical control
Bibliographic record
Abstract
Background: Reactive balance training (RBT) has been previously found to reduce fall risk in individuals with sub-acute stroke; however, our understanding of the effects of RBT on specific balance impairments is lacking.Objective: To quantify changes in common balance reaction impairments in individuals with sub-acute stroke resulting from RBT, relative to traditional balance training, using a prospective cohort study design with a historical control group.Methods: Individuals with sub-acute stroke completed either RBT or traditional balance training as part of their routine care during physiotherapy in inpatient rehabilitation. Reactive balance control was assessed using lean-and-release perturbations pre-intervention, post-intervention, and 6-months post-intervention (follow-up). Individuals with impaired balance reactions (delayed foot-off times, slide steps, and/or a preference for stepping with the preferred limb) at the pre-intervention assessment were identified using video and force plate data. Outcome measures (foot-off times, frequency of trials with slide steps, and stepping with the preferred limb) from the RBT participants with impaired reactions were compared for each of the three assessments to the mean values for the participants with impaired reactions in the historical control group.Results: Improvements were observed in all outcome measures for the RBT participants between pre-intervention and post-intervention, and/or between post-intervention and follow-up. These improvements were generally equivalent to, if not better than, the improvements demonstrated by the historical control group.Conclusions: Findings further support the use of RBT for post-stroke inpatient rehabilitation, and provide insight into specific balance reaction impairments that are improved by RBT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".